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Can you explain the concept of feature attribution in Explainable AI?
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Answer / Mohd Tauhid
Feature attribution is a method used in Explainable AI (XAI) to identify and quantify the contribution of individual features or inputs towards the output of a machine learning model. This process provides insights into how the model makes decisions, making it easier for humans to understand and trust the predictions. For instance, feature attribution can reveal which attributes in an image are most relevant to a model's classification of that image.
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